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Open nowPosted 116 days ago

重定向算法实习生

agirobot/internrecruitment367 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now重定向算法实习生agirobot/internrecruitment · Shenzhen, Guangdong, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on agirobot/internrecruitment's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. agirobot/internrecruitment postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 116 days ago

agirobot/internrecruitment median: 2 days open

The posting

岗位职责 1. 重定向算法研发：研究并实现基于逆运动学（IK）、运动学优化或神经网络的人体到机器人动作映射方案。 2. 数据处理与特征构建：处理动作捕捉（MoCap）、RGBD、IMU等多模态人体姿态数据，完成骨骼重定向所需的数据预处理与特征提取。 3. 运动学建模：分析人机骨骼拓扑差异（自由度数量、关节类型、比例），设计合理的映射规则与约束条件。 4. 仿真与实机验证：在 MuJoCo / Isaac Sim 等仿真平台上验证算法效果，并协助推进实机部署与调试。 5. 效果评估：建立重定向质量量化指标体系（关节误差、末端执行器位置误差、运动平滑度等），持续迭代优化。

掌握机器人正/逆运动学基本原理，理解 DH 参数、雅可比矩阵及关节空间与笛卡尔空间的转换关系。 Python 、c++编程熟练，能使用 NumPy / SciPy 完成数值计算与数据处理。 有 MuJoCo、Isaac Sim、Gazebo 或 PyBullet 至少一款仿真平台的使用经验，能读写 URDF / MJCF 模型文件，熟悉 ROS / ROS2 基本开发流程。 加分项 了解约束优化方法（QP、NLSQ 等），能使用 OSQP、CasADi 等工具求解 IK 问题者优先。 有强化学习或模仿学习在运动控制中的应用经验，熟悉 PyTorch 者加分。 有 MoCap 数据处理经验，或了解 MediaPipe、OpenPose 等人体姿态估计工具者加分。 有双足/人形机器人全身控制（WBC）相关项目经验者优先考虑。

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